For release 10:00 a.m. (EDT), Wednesday, March 9, 2016
USDL-16-0462
Technical Information: (202) 691-6567 • [email protected] • www.bls.gov/cew
Media Contact:
(202) 691-5902 • [email protected]
COUNTY EMPLOYMENT AND WAGES
Third Quarter 2015
From September 2014 to September 2015, employment increased in 312 of the 342 largest U.S.
counties (counties with 75,000 or more jobs in 2014), the U.S. Bureau of Labor Statistics reported today.
Williamson, Tenn., had the largest percentage increase, with a gain of 6.5 percent over the year, above
the national job growth of 1.9 percent. Within Williamson, the largest employment increase occurred in
professional and business services, which gained 2,538 jobs over the year (8.8 percent). Ector, Texas,
had the largest over-the-year percentage decrease in employment among the largest counties in the U.S.,
with a loss of 8.3 percent. Within Ector, natural resources and mining had the largest decrease in
employment, with a loss of 3,752 jobs (-28.4 percent). County employment and wage data are compiled
under the Quarterly Census of Employment and Wages (QCEW) program, which produces detailed
information on county employment and wages within 6 months after the end of each quarter.
The U.S. average weekly wage increased 2.6 percent over the year, growing to $974 in the third quarter
of 2015. Rockland, N.Y., had the largest over-the-year percentage increase in average weekly wages
with a gain of 24.9 percent. Within Rockland, an average weekly wage gain of $3,170, or 220.4 percent,
in manufacturing made the largest contribution to the county’s increase in average weekly wages.
Midland, Texas, experienced the largest percentage decrease in average weekly wages with a loss of 6.7
percent over the year. Within Midland, natural resources and mining had the largest impact on the
county’s average weekly wage decline with a decrease of $163 (-8.1 percent) over the year.
Chart 1. Large counties ranked by percent increase in
employment, September 2014-15
(U.S. average = 1.9 percent)
Chart 2. Large counties ranked by percent increase in
average weekly wages, third quarter 2014-15
(U.S. average = 2.6 percent)
Percent
Percent
25
7
20
15
6
10
5
5
Williamson,
Tenn.
Utah,
Utah
Denton,
Texas
Chesterfield,
Va.
Lee,
Fla.
Rockland,
N.Y.
Lake,
Ill.
Onondaga, Washington,
N.Y.
Ore.
Marin,
Calif.
Santa Cruz,
Calif.
Table A. Large counties ranked by September 2015 employment, September 2014-15 employment increase, and
September 2014-15 percent increase in employment
Employment in large counties
September 2015 employment
(thousands)
United States
Los Angeles, Calif.
Cook, Ill.
New York, N.Y.
Harris, Texas
Maricopa, Ariz.
Dallas, Texas
Orange, Calif.
San Diego, Calif.
King, Wash.
Miami-Dade, Fla.
140,442.2
4,261.8
2,535.6
2,370.4
2,287.6
1,824.7
1,616.8
1,524.0
1,384.0
1,292.1
1,076.1
Increase in employment,
September 2014-15
(thousands)
United States
Percent increase in employment,
September 2014-15
2,679.6
Los Angeles, Calif.
Maricopa, Ariz.
Dallas, Texas
Orange, Calif.
New York, N.Y.
King, Wash.
Santa Clara, Calif.
San Diego, Calif.
Cook, Ill.
San Francisco, Calif.
93.0
65.4
62.9
49.0
48.3
42.0
39.8
38.7
37.8
34.0
United States
1.9
Williamson, Tenn.
Utah, Utah
Denton, Texas
Chesterfield, Va.
Lee, Fla.
Osceola, Fla.
Loudoun, Va.
San Francisco, Calif.
Clay, Mo.
San Mateo, Calif.
6.5
6.3
6.1
5.7
5.5
5.4
5.3
5.2
5.1
5.0
Large County Employment
In September 2015, national employment was 140.4 million (as measured by the QCEW program). Over
the year, employment increased 1.9 percent, or 2.7 million. In September 2015, the 342 U.S. counties
with 75,000 or more jobs accounted for 72.2 percent of total U.S. employment and 77.3 percent of total
wages. These 342 counties had a net job growth of 2.1 million over the year, accounting for 79.6 percent
of the overall U.S. employment increase. (See chart 3.)
Williamson, Tenn., had the largest percentage increase in employment (6.5 percent) among the largest
U.S. counties. The five counties with the largest increases in employment levels were Los Angeles,
Calif.; Maricopa, Ariz.; Dallas, Texas; Orange, Calif.; and New York, N.Y. These counties had a
combined over-the-year employment gain of 318,600 jobs, which was 11.9 percent of the overall job
increase for the U.S. (See table A.)
Employment declined in 24 of the largest counties from September 2014 to September 2015. Ector,
Texas, had the largest over-the-year percentage decrease in employment (-8.3 percent). Midland, Texas,
had the second largest percentage decrease in employment, followed by Gregg, Texas; Lafayette, La.;
and Atlantic, N.J. (See table 1.)
-2-
Table B. Large counties ranked by third quarter 2015 average weekly wages, third quarter 2014-15
increase in average weekly wages, and third quarter 2014-15 percent increase in average weekly wages
Average weekly wage in large counties
Average weekly wage,
third quarter 2015
United States
Santa Clara, Calif.
San Mateo, Calif.
New York, N.Y.
San Francisco, Calif.
Washington, D.C.
Arlington, Va.
Suffolk, Mass.
King, Wash.
Fairfax, Va.
Somerset, N.J.
Increase in average weekly
wage, third quarter 2014-15
$974
$2,090
1,894
1,829
1,712
1,667
1,587
1,559
1,463
1,462
1,447
United States
Percent increase in average
weekly wage, third
quarter 2014-15
$25
Rockland, N.Y.
Lake, Ill.
Washington, Ore.
Marin, Calif.
Santa Clara, Calif.
San Mateo, Calif.
Somerset, N.J.
Onondaga, N.Y.
Davidson, Tenn.
Williamson, Tenn.
$233
136
78
68
65
62
60
56
54
54
United States
Rockland, N.Y.
Lake, Ill.
Onondaga, N.Y.
Washington, Ore.
Marin, Calif.
Santa Cruz, Calif.
Genesee, Mich.
Davidson, Tenn.
Placer, Calif.
Williamson, Tenn.
2.6
24.9
11.7
6.5
6.4
6.1
6.1
5.6
5.5
5.4
5.2
Large County Average Weekly Wages
Average weekly wages for the nation increased to $974, a 2.6 percent increase, during the year ending in
the third quarter of 2015. Among the 342 largest counties, 319 had over-the-year increases in average
weekly wages. (See chart 4.) Rockland, N.Y., had the largest percentage wage increase among the
largest U.S. counties (24.9 percent).
Of the 342 largest counties, 20 experienced over-the-year decreases in average weekly wages. Midland,
Texas, had the largest percentage decrease in average weekly wages, with a loss of 6.7 percent. Ector,
Texas, had the second largest percentage decrease in average weekly wages, followed by Lafayette, La.;
Stark, Ohio; and Gregg, Texas. (See table 1.)
Ten Largest U.S. Counties
All of the 10 largest counties had over-the-year percentage increases in employment in September
2015. Dallas, Texas, had the largest gain (4.0 percent). Within Dallas, trade, transportation, and utilities
had the largest over-the-year employment level increase, with a gain of 17,638 jobs, or 5.6 percent.
Harris, Texas, had the smallest percentage increase in employment (0.8 percent) among the 10 largest
counties. (See table 2.)
Average weekly wages increased over the year in all of the 10 largest U.S. counties. San Diego, Calif.,
experienced the largest percentage gain in average weekly wages (4.2 percent). Within San Diego,
professional and business services had the largest impact on the county’s average weekly wage growth.
Within this industry, average weekly wages increased by $120, or 8.4 percent, over the year. Harris,
Texas, had the smallest percentage gain in average weekly wages (0.1 percent) among the 10 largest
counties.
-3-
For More Information
The tables and charts included in this release contain data for the nation and for the 342 U.S. counties
with annual average employment levels of 75,000 or more in 2014. September 2015 employment and
2015 third quarter average weekly wages for all states are provided in table 3 of this release.
The employment and wage data by county are compiled under the QCEW program, also known as the
ES-202 program. The data are derived from reports submitted by every employer subject to
unemployment insurance (UI) laws. The 9.6 million employer reports cover 140.4 million full- and parttime workers. The QCEW program provides a quarterly and annual universe count of establishments,
employment, and wages at the county, MSA, state, and national levels by detailed industry. Data for the
third quarter of 2015 will be available electronically later at www.bls.gov/cew/. For additional
information about the quarterly employment and wages data, please read the Technical Note. Additional
information about the QCEW data may be obtained by calling (202) 691-6567.
Several BLS regional offices are issuing QCEW news releases targeted to local data users. For links to
these releases, see www.bls.gov/cew/cewregional.htm.
The County Employment and Wages release for fourth quarter 2015 is scheduled to be released
on Wednesday, June 8, 2016.
Census Area Name Change Effective with BLS Release of Data for Fourth Quarter of 2015
On July 1, 2015, Wade Hampton, Alaska, was officially renamed Kusilvak, Alaska. This census area
is not part of this release because it has fewer than 75,000 jobs. However, BLS does publish data for
this census area. This name change is not reflected in this quarter’s data release. The census area
name change will be implemented by BLS with the fourth quarter 2015 news release. The name
change will also be retroactively implemented for the third quarter data. Data prior to third quarter
2015 will still be available under Wade Hampton, Alaska.
-4-
Technical Note
These data are the product of a federal-state cooperative program,
the Quarterly Census of Employment and Wages (QCEW) program,
also known as the ES-202 program. The data are derived from summaries of employment and total pay of workers covered by state and
federal unemployment insurance (UI) legislation and provided by
State Workforce Agencies (SWAs). The summaries are a result of
the administration of state unemployment insurance programs that
require most employers to pay quarterly taxes based on the employment and wages of workers covered by UI. QCEW data in this release are based on the 2012 North American Industry Classification
System. Data for 2015 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having
employment levels of 75,000 or greater. In addition, data for San
Juan, Puerto Rico, are provided, but not used in calculating U.S. averages, rankings, or in the analysis in the text. Each year, these large
counties are selected on the basis of the preliminary annual average
of employment for the previous year. The 343 counties presented in
this release were derived using 2014 preliminary annual averages of
employment. For 2015 data, three counties have been added to the
publication tables: Butte, Calif.; Hall, Ga.; and Ector, Texas. These
counties will be included in all 2015 quarterly releases. The counties
in table 2 are selected and sorted each year based on the annual average employment from the preceding year.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
QCEW
Source
Coverage
BED
CES
· Count of UI administrative records
submitted by 9.5 million establishments in first quarter of 2015
· Count of longitudinally-linked UI administrative records submitted by
7.6 million private-sector employers
· Sample survey: 623,000 establishments
· UI and UCFE coverage, including
all employers subject to state and
federal UI laws
· UI coverage, excluding government,
private households, and establishments with zero employment
Nonfarm wage and salary jobs:
· UI coverage, excluding agriculture, private
households, and self-employed workers
· Other employment, including railroads,
religious organizations, and other nonUI-covered jobs
· Quarterly
— 7 months after the end of each
quarter
· Monthly
— Usually first Friday of following
month
Publication fre- · Quarterly
quency
— 6 months after the end of each
quarter
Use of UI file
· Directly summarizes and publishes
each new quarter of UI data
· Links each new UI quarter to longitu- · Uses UI file as a sampling frame and to
dinal database and directly summaannually realign sample-based estimates
rizes gross job gains and losses
to population counts (benchmarking)
Principal
products
· Provides a quarterly and annual uni- · Provides quarterly employer dynam- · Provides current monthly estimates of
verse count of establishments, emics data on establishment openings,
employment, hours, and earnings at the
ployment, and wages at the county,
closings, expansions, and contractions
MSA, state, and national level by indusMSA, state, and national levels by
at the national level by NAICS supertry
detailed industry
sectors and by size of firm, and at the
state private-sector total level
· Future expansions will include data
with greater industry detail and data
at the county and MSA level
Principal uses
· Major uses include:
— Detailed locality data
— Periodic universe counts for
benchmarking sample survey estimates
— Sample frame for BLS establishment surveys
Program Web
sites
· www.bls.gov/cew/
· Major uses include:
— Business cycle analysis
— Analysis of employer dynamics
underlying economic expansions
and contractions
— Analysis of employment expansion and contraction by size of
firm
· www.bls.gov/bdm/
· Major uses include:
— Principal national economic indicator
— Official time series for employment
change measures
— Input into other major economic indicators
· www.bls.gov/ces/
The preliminary QCEW data presented in this release may differ
from data released by the individual states. These potential differences
result from the states' continuing receipt of UI data over time and ongoing review and editing. The individual states determine their data
release timetables.
Differences between QCEW, BED, and CES employment
measures
The Bureau publishes three different establishment-based employment measures for any given quarter. Each of these measures—
QCEW, Business Employment Dynamics (BED), and Current Employment Statistics (CES)—makes use of the quarterly UI employment reports in producing data; however, each measure has a somewhat different universe coverage, estimation procedure, and publication product.
Differences in coverage and estimation methods can result in somewhat different measures of employment change over time. It is important to understand program differences and the intended uses of the
program products. (See table.) Additional information on each program can be obtained from the program Web sites shown in the table.
Coverage
Employment and wage data for workers covered by state UI laws
are compiled from quarterly contribution reports submitted to the
SWAs by employers. For federal civilian workers covered by the Unemployment Compensation for Federal Employees (UCFE) program,
employment and wage data are compiled from quarterly reports submitted by four major federal payroll processing centers on behalf of
all federal agencies, with the exception of a few agencies which still
report directly to the individual SWA. In addition to the quarterly contribution reports, employers who operate multiple establishments
within a state complete a questionnaire, called the "Multiple Worksite
Report," which provides detailed information on the location and industry of each of their establishments. QCEW employment and wage
data are derived from microdata summaries of 9.4 million employer
reports of employment and wages submitted by states to the BLS in
2014. These reports are based on place of employment rather than
place of residence.
UI and UCFE coverage is broad and has been basically comparable
from state to state since 1978, when the 1976 amendments to the Federal Unemployment Tax Act became effective, expanding coverage to
include most state and local government employees. In 2014, UI and
UCFE programs covered workers in 136.6 million jobs. The estimated
131.8 million workers in these jobs (after adjustment for multiple jobholders) represented 96.3 percent of civilian wage and salary employment. Covered workers received $7.017 trillion in pay, representing
93.8 percent of the wage and salary component of personal income
and 40.5 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural workers on small farms, all members of the
Armed Forces, elected officials in most states, most employees of railroads, some domestic workers, most student workers at schools, and
employees of certain small nonprofit organizations.
State and federal UI laws change periodically. These changes may
have an impact on the employment and wages reported by employers
covered under the UI program. Coverage changes may affect the overthe-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who
worked during or received pay for the pay period including the 12th
of the month. With few exceptions, all employees of covered firms are
reported, including production and sales workers, corporation officials, executives, supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also are included.
Average weekly wage values are calculated by dividing quarterly
total wages by the average of the three monthly employment levels
(all employees, as described above) and dividing the result by 13, for
the 13 weeks in the quarter. These calculations are made using unrounded employment and wage values. The average wage values that
can be calculated using rounded data from the BLS database may differ from the averages reported. Included in the quarterly wage data are
non-wage cash payments such as bonuses, the cash value of meals and
lodging when supplied, tips and other gratuities, and, in some states,
employer contributions to certain deferred compensation plans such
as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may reflect fluctuations in average monthly employment and/or total quarterly wages between the current quarter and
prior year levels.
Average weekly wages are affected by the ratio of full-time to parttime workers as well as the number of individuals in high-paying and
low-paying occupations and the incidence of pay periods within a
quarter. For instance, the average weekly wage of the workforce could
increase significantly when there is a large decline in the number of
employees that had been receiving below-average wages. Wages may
include payments to workers not present in the employment counts
because they did not work during the pay period including the 12th of
the month. When comparing average weekly wage levels between industries, states, or quarters, these factors should be taken into consideration.
Wages measured by QCEW may be subject to periodic and sometimes large fluctuations. This variability may be due to calendar effects resulting from some quarters having more pay dates than others.
The effect is most visible in counties with a dominant employer. In
particular, this effect has been observed in counties where government
employers represent a large fraction of overall employment. Similar
calendar effects can result from private sector pay practices. However,
these effects are typically less pronounced for two reasons: employment is less concentrated in a single private employer, and private employers use a variety of pay period types (weekly, biweekly, semimonthly, monthly).
For example, the effect on over-the-year pay comparisons can be
pronounced in federal government due to the uniform nature of federal
payroll processing. Most federal employees are paid on a biweekly
pay schedule. As a result, in some quarters federal wages include six
pay dates, while in other quarters there are seven pay dates. Over-theyear comparisons of average weekly wages may also reflect this calendar effect. Growth in average weekly wages may be attributed, in
part, to a comparison of quarterly wages for the current year, which
include seven pay dates, with year-ago wages that reflect only six pay
dates. An opposite effect will occur when wages in the current quarter
reflecting six pay dates are compared with year-ago wages for a quarter including seven pay dates.
In order to ensure the highest possible quality of data, states verify
with employers and update, if necessary, the industry, location, and
ownership classification of all establishments on a 3-year cycle.
Changes in establishment classification codes resulting from this process are introduced with the data reported for the first quarter of the
year. Changes resulting from improved employer reporting also are
introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are
simply the sums of individual establishment records and reflect the
number of establishments that exist in a county or industry at a point
in time. Establishments can move in or out of a county or industry for
a number of reasons—some reflecting economic events, others reflecting administrative changes. For example, economic change
would come from a firm relocating into the county; administrative
change would come from a company correcting its county designation.
The over-the-year changes of employment and wages presented in
this release have been adjusted to account for most of the administrative corrections made to the underlying establishment reports. This is
done by modifying the prior-year levels used to calculate the over-theyear changes. Percent changes are calculated using an adjusted version of the final 2014 quarterly data as the base data. The adjusted
prior-year levels used to calculate the over-the-year percent change in
employment and wages are not published. These adjusted prior-year
levels do not match the unadjusted data maintained on the BLS Web
site. Over-the-year change calculations based on data from the Web
site, or from data published in prior BLS news releases, may differ
substantially from the over-the-year changes presented in this news
release.
The adjusted data used to calculate the over-the-year change
measures presented in this release account for most of the administrative changes—those occurring when employers update the industry,
location, and ownership information of their establishments. The most
common adjustments for administrative change are the result of updated information about the county location of individual establishments. Included in these adjustments are administrative changes involving the classification of establishments that were previously reported in the unknown or statewide county or unknown industry categories. Adjusted data account for improvements in reporting employment and wages for individual and multi-unit establishments. To accomplish this, adjustments were implemented to account for: administrative changes caused by multi-unit employers who start reporting
for each individual establishment rather than as a single entity (first
quarter of 2008); selected large administrative changes in employment
and wages (second quarter of 2011); and state verified improvements
in reporting of employment and wages (third quarter of 2014). These
adjustments allow QCEW to include county employment and wage
growth rates in this news release that would otherwise not meet publication standards.
The adjusted data used to calculate the over-the-year change
measures presented in any County Employment and Wages news release are valid for comparisons between the starting and ending points
(a 12-month period) used in that particular release. Comparisons may
not be valid for any time period other than the one featured in a release
even if the changes were calculated using adjusted data.
County definitions are assigned according to Federal Information
Processing Standards Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after approval by the
Secretary of Commerce pursuant to Section 5131 of the Information
Technology Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106. Areas shown as counties include those designated as independent cities in some jurisdictions and,
in Alaska, those designated as census areas where counties have not
been created. County data also are presented for the New England
states for comparative purposes even though townships are the more
common designation used in New England (and New Jersey). The regions referred to in this release are defined as census regions.
Additional statistics and other information
Employment and Wages Annual Averages Online features comprehensive information by detailed industry on establishments, employment, and wages for the nation and all states. The 2014 edition of this
publication, which was published in September 2015, contains selected data produced by Business Employment Dynamics (BED) on
job gains and losses, as well as selected data from the first quarter
2015 version of this news release. Tables and additional content from
the 2014 edition of Employment and Wages Annual Averages Online
are now available at http://www.bls.gov/cew/cewbultn14.htm. The
2015 edition of Employment and Wages Annual Averages Online will
be available in September 2016.
News releases on quarterly measures of gross job flows also are
available upon request from the Division of Administrative Statistics
and Labor Turnover (Business Employment Dynamics), telephone
(202)
691-6467;
(http://www.bls.gov/bdm/);
(e-mail:
[email protected]).
Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; TDD
message referral phone number: 1-800-877-8339.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
United States⁴..............................
9,633.8
140,442.2
1.9
-
$974
2.6
-
Jefferson, AL................................
Madison, AL.................................
Mobile, AL....................................
Montgomery, AL...........................
Shelby, AL....................................
Tuscaloosa, AL.............................
Anchorage Borough, AK...............
Maricopa, AZ................................
Pima, AZ.......................................
Benton, AR...................................
17.8
9.2
9.7
6.3
5.5
4.4
8.4
95.7
19.1
5.9
338.3
186.5
166.6
128.7
83.6
92.2
156.9
1,824.7
354.7
111.7
0.7
1.7
0.4
0.7
1.0
1.6
0.5
3.7
0.6
4.8
266
186
292
266
231
192
284
45
276
12
962
1,053
835
819
914
811
1,084
929
816
949
0.8
1.5
1.7
1.0
4.2
-0.4
1.6
1.4
0.0
2.4
311
265
253
300
33
326
259
274
320
178
Pulaski, AR...................................
Washington, AR...........................
Alameda, CA................................
Butte, CA.....................................
Contra Costa, CA.........................
Fresno, CA...................................
Kern, CA.......................................
Los Angeles, CA...........................
Marin, CA.....................................
Monterey, CA...............................
14.5
5.8
59.6
8.0
30.9
32.5
17.7
457.6
12.3
13.2
247.2
101.3
734.5
79.1
349.0
375.9
323.2
4,261.8
112.3
202.3
1.7
4.2
3.3
1.8
2.4
2.2
-0.5
2.2
2.6
2.3
186
22
71
172
128
143
325
143
117
137
869
786
1,289
731
1,168
772
828
1,074
1,185
825
2.1
2.3
2.3
3.8
3.2
3.3
-0.5
3.7
6.1
3.3
215
193
193
53
91
82
328
60
5
82
Orange, CA..................................
Placer, CA....................................
Riverside, CA...............................
Sacramento, CA...........................
San Bernardino, CA.....................
San Diego, CA..............................
San Francisco, CA.......................
San Joaquin, CA..........................
San Luis Obispo, CA....................
San Mateo, CA.............................
112.3
12.0
57.0
54.3
53.8
104.5
59.2
17.1
10.1
27.1
1,524.0
149.9
659.5
629.7
686.9
1,384.0
684.1
238.6
114.6
387.8
3.3
3.9
4.8
2.8
3.2
2.9
5.2
4.2
2.9
5.0
71
39
12
104
81
101
8
22
101
10
1,077
989
781
1,068
815
1,071
1,712
834
814
1,894
2.1
5.4
3.0
1.6
3.0
4.2
1.4
4.0
4.1
3.4
215
9
117
259
117
33
274
44
37
77
Santa Barbara, CA.......................
Santa Clara, CA...........................
Santa Cruz, CA............................
Solano, CA...................................
Sonoma, CA.................................
Stanislaus, CA..............................
Tulare, CA....................................
Ventura, CA..................................
Yolo, CA.......................................
Adams, CO...................................
14.9
68.6
9.4
10.6
19.3
14.8
9.5
25.5
6.4
10.1
197.6
1,026.6
103.4
132.7
200.6
183.5
158.9
313.4
102.8
194.1
1.6
4.0
2.3
3.5
2.8
3.2
1.7
1.5
1.1
4.1
192
32
137
58
104
81
186
204
227
25
934
2,090
888
981
935
840
685
961
1,006
952
3.9
3.2
6.1
2.4
4.7
4.3
3.6
1.6
3.1
3.0
47
91
5
178
19
30
64
259
104
117
Arapahoe, CO..............................
Boulder, CO..................................
Denver, CO..................................
Douglas, CO.................................
El Paso, CO..................................
Jefferson, CO...............................
Larimer, CO..................................
Weld, CO......................................
Fairfield, CT.................................
Hartford, CT..................................
21.0
14.4
29.9
11.2
18.2
19.2
11.3
6.7
34.7
27.2
318.6
173.8
483.7
112.9
259.7
230.2
149.5
101.2
422.5
506.0
2.9
2.7
3.6
3.3
3.5
2.8
3.7
-1.3
0.8
0.4
101
112
49
71
58
104
45
331
252
292
1,117
1,158
1,194
1,033
876
992
892
861
1,406
1,142
1.3
3.1
2.0
-1.0
1.9
4.5
3.8
-1.4
0.4
1.9
279
104
228
333
241
25
53
335
316
241
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
New Haven, CT............................
New London, CT..........................
New Castle, DE............................
Washington, DC...........................
Alachua, FL..................................
Brevard, FL...................................
Broward, FL..................................
Collier, FL.....................................
Duval, FL.....................................
Escambia, FL...............................
23.5
7.3
18.8
38.2
6.8
15.0
66.3
12.9
27.7
8.0
361.0
122.6
284.0
743.6
124.4
193.9
759.7
128.7
474.0
126.6
0.0
0.2
1.9
1.4
1.9
1.9
2.4
4.0
3.6
1.5
313
307
162
211
162
162
128
32
49
204
$1,021
943
1,066
1,667
805
873
898
815
909
760
3.2
1.6
-0.7
2.3
2.0
2.5
3.3
1.2
2.0
3.5
91
259
332
193
228
165
82
286
228
72
Hillsborough, FL...........................
Lake, FL.......................................
Lee, FL.........................................
Leon, FL.......................................
Manatee, FL.................................
Marion, FL....................................
Miami-Dade, FL............................
Okaloosa, FL................................
Orange, FL...................................
Osceola, FL..................................
39.4
7.6
20.4
8.3
10.0
8.1
93.2
6.2
38.7
6.2
641.6
90.2
236.2
142.4
111.9
96.4
1,076.1
80.2
765.8
85.1
3.6
4.0
5.5
0.2
4.4
1.3
2.8
2.1
4.0
5.4
49
32
5
307
18
217
104
145
32
6
914
680
766
795
740
658
924
816
854
671
2.0
3.7
3.1
2.4
4.8
2.0
3.9
4.7
4.1
2.8
228
60
104
178
13
228
47
19
37
138
Palm Beach, FL............................
Pasco, FL.....................................
Pinellas, FL...................................
Polk, FL........................................
Sarasota, FL................................
Seminole, FL................................
Volusia, FL...................................
Bibb, GA.......................................
Chatham, GA................................
Clayton, GA..................................
52.7
10.3
31.4
12.5
15.2
14.1
13.7
4.5
8.4
4.4
559.3
109.2
407.8
203.5
158.1
174.9
160.7
82.9
146.7
117.0
3.6
3.1
2.8
3.7
3.6
3.6
3.0
1.4
3.2
3.3
49
89
104
45
49
49
95
211
81
71
924
676
846
740
777
803
697
760
821
912
2.2
4.5
2.3
1.5
3.2
3.2
5.0
3.0
2.5
2.5
204
25
193
265
91
91
11
117
165
165
Cobb, GA......................................
DeKalb, GA.................................
Fulton, GA....................................
Gwinnett, GA................................
Hall, GA.......................................
Muscogee, GA..............................
Richmond, GA..............................
Honolulu, HI..................................
Ada, ID.........................................
Champaign, IL..............................
23.2
19.2
45.8
26.2
4.6
4.9
4.8
25.2
14.1
4.6
334.6
291.1
796.3
335.6
80.5
93.3
104.7
462.1
219.2
90.3
3.1
2.5
3.2
2.8
4.3
-0.7
2.1
1.1
4.1
-0.2
89
124
81
104
19
328
145
227
25
319
1,006
977
1,266
962
825
761
819
932
841
877
2.2
3.1
2.3
2.2
3.3
1.9
2.4
3.1
1.1
3.4
204
104
193
204
82
241
178
104
294
77
Cook, IL........................................
DuPage, IL.................................
Kane, IL........................................
Lake, IL........................................
McHenry, IL..................................
McLean, IL....................................
Madison, IL...................................
Peoria, IL......................................
St. Clair, IL....................................
Sangamon, IL...............................
165.4
40.2
14.5
23.8
9.3
4.0
6.4
4.9
5.8
5.5
2,535.6
603.6
209.2
334.6
97.7
84.7
98.8
100.7
93.3
129.3
1.5
0.6
0.5
0.7
0.3
0.5
-0.4
0.7
1.0
-0.5
204
276
284
266
301
284
324
266
231
325
1,108
1,121
867
1,298
808
895
794
910
787
1,001
3.4
4.8
4.5
11.7
2.9
0.3
3.1
3.8
2.3
1.1
77
13
25
2
129
317
104
53
193
294
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
Will, IL..........................................
Winnebago, IL..............................
Allen, IN........................................
Elkhart, IN.....................................
Hamilton, IN..................................
Lake, IN........................................
Marion, IN.....................................
St. Joseph, IN...............................
Tippecanoe, IN.............................
Vanderburgh, IN...........................
17.1
7.1
8.7
4.7
8.9
10.3
23.8
5.8
3.3
4.7
224.7
128.1
183.8
125.0
134.8
187.8
586.7
122.4
82.1
106.4
1.9
0.0
2.4
3.2
3.9
0.2
1.8
3.1
0.9
0.5
162
313
128
81
39
307
172
89
243
284
$858
811
796
790
913
841
966
795
831
786
2.4
1.8
2.7
1.2
2.6
-0.6
1.7
2.3
3.6
3.6
178
247
147
286
154
329
253
193
64
64
Black Hawk, IA............................
Johnson, IA..................................
Linn, IA.........................................
Polk, IA........................................
Scott, IA........................................
Johnson, KS.................................
Sedgwick, KS...............................
Shawnee, KS................................
Wyandotte, KS.............................
Boone, KY...................................
3.9
4.1
6.6
16.8
5.5
22.4
12.7
5.0
3.4
4.3
74.0
82.1
129.4
289.6
91.6
334.6
247.5
97.5
90.4
81.9
-2.5
1.0
0.6
0.8
0.8
1.9
1.0
0.5
2.3
4.3
335
231
276
252
252
162
231
284
137
19
808
920
929
981
799
968
831
783
942
826
0.9
3.0
1.5
2.4
4.7
1.3
0.8
2.1
3.2
2.6
305
117
265
178
19
279
311
215
91
154
Fayette, KY...................................
Jefferson, KY................................
Caddo, LA....................................
Calcasieu, LA...............................
East Baton Rouge, LA..................
Jefferson, LA................................
Lafayette, LA................................
Orleans, LA..................................
St. Tammany, LA..........................
Cumberland, ME..........................
10.6
24.8
7.3
5.0
14.9
13.6
9.3
12.1
7.8
13.1
190.8
453.3
114.9
92.0
270.6
192.5
136.7
190.0
86.2
176.9
2.6
1.6
0.4
3.3
0.5
-0.2
-3.9
3.2
3.8
1.0
117
192
292
71
284
319
337
81
42
231
879
933
799
881
914
876
919
922
833
857
4.4
3.9
0.6
0.9
3.3
1.9
-3.2
-0.2
1.8
3.1
29
47
314
305
82
241
339
322
247
104
Anne Arundel, MD........................
Baltimore, MD...............................
Frederick, MD...............................
Harford, MD..................................
Howard, MD.................................
Montgomery, MD..........................
Prince George's, MD....................
Baltimore City, MD.......................
Barnstable, MA.............................
Bristol, MA....................................
15.0
21.2
6.4
5.7
9.9
32.7
15.7
13.6
9.3
17.0
261.8
371.9
99.4
90.7
166.0
461.1
308.6
335.1
101.0
221.9
2.4
1.2
2.4
1.4
1.8
0.9
1.0
-0.2
1.7
0.3
128
221
128
211
172
243
231
319
186
301
1,048
980
911
923
1,181
1,277
1,058
1,152
808
882
2.9
1.9
0.9
2.6
-1.3
2.7
2.1
2.3
3.3
5.0
129
241
305
154
334
147
215
193
82
11
Essex, MA....................................
Hampden, MA..............................
Middlesex, MA..............................
Norfolk, MA...................................
Plymouth, MA...............................
Suffolk, MA...................................
Worcester, MA..............................
Genesee, MI.................................
Ingham, MI...................................
Kalamazoo, MI.............................
23.7
17.2
53.3
24.7
15.1
27.5
23.8
7.0
6.0
5.1
320.9
204.1
874.9
344.2
188.3
639.1
334.7
132.7
147.3
114.7
1.0
0.8
2.0
1.4
0.8
2.0
0.8
0.0
0.4
0.8
231
252
151
211
252
151
252
313
292
252
1,009
884
1,419
1,112
909
1,559
969
816
898
898
0.8
2.9
2.6
2.5
4.0
3.1
3.2
5.6
1.8
2.4
311
129
154
165
44
104
91
7
247
178
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
Kent, MI.......................................
Macomb, MI..................................
Oakland, MI..................................
Ottawa, MI....................................
Saginaw, MI..................................
Washtenaw, MI.............................
Wayne, MI....................................
Anoka, MN....................................
Dakota, MN..................................
Hennepin, MN..............................
14.1
17.5
38.8
5.6
4.0
8.2
30.6
6.6
9.3
37.1
373.7
317.3
709.0
122.8
84.8
202.0
700.9
119.3
184.0
888.5
3.3
2.4
1.6
3.1
1.0
0.9
0.9
0.7
0.3
2.0
71
128
192
89
231
243
243
266
301
151
$875
950
1,061
818
777
1,052
1,059
968
944
1,198
3.6
1.1
3.0
2.0
2.4
2.7
3.1
3.5
2.8
2.0
64
294
117
228
178
147
104
72
138
228
Olmsted, MN................................
Ramsey, MN.................................
St. Louis, MN................................
Stearns, MN.................................
Washington, MN...........................
Harrison, MS................................
Hinds, MS.....................................
Boone, MO...................................
Clay, MO......................................
Greene, MO..................................
3.2
12.7
5.1
4.1
5.2
4.4
5.9
4.9
5.4
8.5
94.2
330.0
97.7
84.9
79.4
83.2
120.0
92.5
99.2
162.0
1.7
1.2
-0.2
0.2
2.8
0.6
0.8
1.8
5.1
1.1
186
221
319
307
104
276
252
172
9
227
1,113
1,073
836
825
810
701
832
795
856
753
3.4
1.7
1.6
4.8
3.6
1.2
2.2
3.7
3.0
3.9
77
253
259
13
64
286
204
60
117
47
Jackson, MO................................
St. Charles, MO............................
St. Louis, MO................................
St. Louis City, MO........................
Yellowstone, MT...........................
Douglas, NE.................................
Lancaster, NE...............................
Clark, NV.....................................
Washoe, NV.................................
Hillsborough, NH..........................
21.0
8.9
35.8
12.6
6.4
18.9
10.2
53.9
14.4
12.3
358.0
141.2
593.3
228.3
81.5
333.2
167.3
913.4
205.1
197.5
2.0
4.8
1.6
1.9
2.4
2.1
1.6
3.5
4.3
1.3
151
12
192
162
128
145
192
58
19
217
989
774
1,004
1,045
845
928
797
843
877
1,031
2.6
1.2
0.9
1.6
4.7
4.7
3.8
2.4
2.5
1.5
154
286
305
259
19
19
53
178
165
265
Rockingham, NH..........................
Atlantic, NJ...................................
Bergen, NJ...................................
Burlington, NJ...............................
Camden, NJ.................................
Essex, NJ....................................
Gloucester, NJ..............................
Hudson, NJ...................................
Mercer, NJ....................................
Middlesex, NJ..............................
10.8
6.5
32.8
10.9
11.9
20.1
6.2
14.2
11.1
21.8
146.0
127.8
444.0
197.9
198.5
333.1
103.2
244.8
239.9
404.6
2.7
-2.8
0.6
1.1
2.0
0.6
1.8
3.2
2.7
1.0
112
336
276
227
151
276
172
81
112
231
938
814
1,135
994
943
1,177
835
1,280
1,234
1,142
2.2
2.5
2.9
3.0
4.8
2.0
2.1
1.0
1.3
2.1
204
165
129
117
13
228
215
300
279
215
Monmouth, NJ..............................
Morris, NJ.....................................
Ocean, NJ....................................
Passaic, NJ..................................
Somerset, NJ...............................
Union, NJ.....................................
Bernalillo, NM...............................
Albany, NY...................................
Bronx, NY.....................................
Broome, NY..................................
19.9
16.8
12.8
12.3
10.0
14.2
18.1
10.5
18.7
4.6
255.5
286.4
163.4
164.1
182.4
217.0
320.1
228.9
297.9
86.6
2.6
1.6
2.7
-0.6
1.2
(⁵)
1.2
0.5
0.3
-1.6
117
192
112
327
221
221
284
301
333
932
1,380
766
944
1,447
1,188
842
1,038
938
753
1.7
2.4
1.7
2.6
4.3
(⁵)
1.3
3.1
2.4
2.2
253
178
253
154
30
279
104
178
204
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
Dutchess, NY...............................
Erie, NY........................................
Kings, NY.....................................
Monroe, NY..................................
Nassau, NY..................................
New York, NY...............................
Oneida, NY...................................
Onondaga, NY..............................
Orange, NY..................................
Queens, NY..................................
8.5
24.8
60.5
18.8
54.2
129.9
5.4
13.1
10.3
51.6
111.4
466.1
658.2
379.9
615.4
2,370.4
104.5
243.9
139.7
637.6
1.6
0.7
3.4
0.9
1.4
2.1
0.7
0.4
0.9
3.5
192
266
66
243
211
145
266
292
243
58
$926
856
835
929
1,063
1,829
740
913
807
930
-0.6
2.4
2.1
2.5
3.6
2.5
-0.3
6.5
3.9
3.3
329
178
215
165
64
165
323
3
47
82
Richmond, NY..............................
Rockland, NY...............................
Saratoga, NY................................
Suffolk, NY...................................
Westchester, NY..........................
Buncombe, NC.............................
Catawba, NC................................
Cumberland, NC...........................
Durham, NC.................................
Forsyth, NC..................................
9.8
10.5
5.9
52.7
36.7
8.6
4.3
6.3
8.0
9.4
113.1
119.7
83.4
651.7
421.4
125.2
83.5
116.8
190.5
181.9
2.0
2.6
2.4
1.6
2.0
3.4
1.8
0.1
1.7
1.8
151
117
128
192
151
66
172
311
186
172
877
1,168
864
1,053
1,222
760
746
767
1,231
886
4.3
24.9
2.0
2.1
1.3
4.0
4.2
2.7
2.9
-0.3
30
1
228
215
279
44
33
147
129
323
Guilford, NC..................................
Mecklenburg, NC..........................
New Hanover, NC........................
Wake, NC.....................................
Cass, ND......................................
Butler, OH.....................................
Cuyahoga, OH..............................
Delaware, OH...............................
Franklin, OH.................................
Hamilton, OH................................
14.3
35.5
7.7
32.0
6.9
7.6
35.5
4.9
30.7
23.4
277.3
638.2
107.7
514.6
116.9
146.4
713.1
84.8
722.9
509.0
2.5
3.7
3.8
4.0
0.8
2.3
0.7
0.8
2.1
1.9
124
45
42
32
252
137
266
252
145
162
857
1,119
769
983
910
850
985
929
982
1,055
1.5
4.2
2.8
2.5
1.3
1.8
1.1
1.0
3.5
2.2
265
33
138
165
279
247
294
300
72
204
Lake, OH......................................
Lorain, OH....................................
Lucas, OH....................................
Mahoning, OH..............................
Montgomery, OH..........................
Stark, OH.....................................
Summit, OH.................................
Warren, OH.................................
Cleveland, OK..............................
Oklahoma, OK..............................
6.2
6.1
10.1
5.9
11.9
8.6
14.1
4.7
5.5
27.2
94.7
96.4
208.7
98.0
249.6
158.4
264.7
88.6
82.0
451.6
0.3
-0.9
1.8
-1.6
1.4
0.3
0.6
3.1
2.0
1.0
301
329
172
333
211
301
276
89
151
231
795
775
839
707
837
740
876
854
719
934
1.5
1.4
1.2
3.8
3.0
-2.1
3.2
3.4
1.1
-1.4
265
274
286
53
117
338
91
77
294
335
Tulsa, OK.....................................
Clackamas, OR............................
Jackson, OR................................
Lane, OR......................................
Marion, OR...................................
Multnomah, OR............................
Washington, OR...........................
Allegheny, PA...............................
Berks, PA.....................................
Bucks, PA.....................................
22.1
14.1
7.0
11.7
10.1
32.7
18.3
35.5
8.9
19.8
347.9
153.0
84.8
147.7
150.2
481.4
275.3
687.5
171.3
255.6
0.8
3.0
3.5
2.6
3.6
3.4
2.5
0.4
1.8
0.7
252
95
58
117
49
66
124
292
172
266
904
926
764
775
788
1,006
1,288
1,051
866
909
1.2
4.8
4.1
2.9
3.7
2.9
6.4
2.6
1.5
1.8
286
13
37
129
60
129
4
154
265
247
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
Butler, PA.....................................
Chester, PA..................................
Cumberland, PA...........................
Dauphin, PA................................
Delaware, PA...............................
Erie, PA........................................
Lackawanna, PA..........................
Lancaster, PA...............................
Lehigh, PA....................................
Luzerne, PA..................................
5.0
15.3
6.3
7.4
13.9
7.1
5.8
13.2
8.6
7.5
85.6
244.7
131.2
178.0
218.0
126.0
97.3
230.9
185.2
142.9
0.4
1.2
2.7
0.5
0.8
0.9
-0.2
2.0
1.5
-0.1
292
221
112
284
252
243
319
151
204
317
$920
1,208
883
962
1,010
775
749
815
938
779
3.5
4.1
2.0
2.4
2.0
2.8
1.9
3.2
1.4
2.6
72
37
228
178
228
138
241
91
274
154
Montgomery, PA...........................
Northampton, PA..........................
Philadelphia, PA...........................
Washington, PA............................
Westmoreland, PA.......................
York, PA.......................................
Providence, RI..............................
Charleston, SC.............................
Greenville, SC..............................
Horry, SC.....................................
27.4
6.7
34.9
5.5
9.3
9.0
17.5
13.8
13.8
8.6
479.5
108.5
651.7
87.3
134.1
176.2
283.8
235.9
257.7
121.1
1.8
1.9
0.9
-1.3
0.6
2.0
1.0
3.4
3.5
3.0
172
162
243
331
276
151
231
66
58
95
1,158
849
1,160
948
785
849
961
873
859
598
2.0
3.2
3.0
0.9
2.1
3.2
2.6
4.1
2.4
3.6
228
91
117
305
215
91
154
37
178
64
Lexington, SC...............................
Richland, SC................................
Spartanburg, SC...........................
York, SC.......................................
Minnehaha, SD.............................
Davidson, TN................................
Hamilton, TN................................
Knox, TN......................................
Rutherford, TN..............................
Shelby, TN....................................
6.4
9.6
6.0
5.1
7.0
20.7
9.2
11.6
5.1
19.9
112.8
214.1
128.1
84.9
123.5
459.2
194.7
233.2
117.2
483.8
4.1
2.1
3.0
4.1
1.5
3.3
3.0
1.6
3.9
1.5
25
145
95
25
204
71
95
192
39
204
741
833
814
763
850
1,030
865
834
843
979
2.1
2.3
2.8
0.5
3.3
5.5
4.5
2.3
2.1
1.5
215
193
138
315
82
8
25
193
215
265
Williamson, TN.............................
Bell, TX.........................................
Bexar, TX.....................................
Brazoria, TX.................................
Brazos, TX....................................
Cameron, TX................................
Collin, TX......................................
Dallas, TX.....................................
Denton, TX..................................
Ector, TX.....................................
7.8
5.1
38.2
5.4
4.3
6.4
22.4
73.2
13.4
4.0
116.9
116.2
821.4
103.4
99.8
135.7
366.9
1,616.8
221.4
72.0
6.5
4.2
3.3
4.0
4.5
1.2
4.9
4.0
6.1
-8.3
1
22
71
32
16
221
11
32
3
340
1,101
823
874
992
734
615
1,126
1,157
885
1,037
5.2
2.6
2.2
2.8
-0.4
2.2
2.5
1.4
3.0
-4.9
10
154
204
138
326
204
165
274
117
340
El Paso, TX..................................
Fort Bend, TX...............................
Galveston, TX...............................
Gregg, TX.....................................
Harris, TX.....................................
Hidalgo, TX...................................
Jefferson, TX................................
Lubbock, TX.................................
McLennan, TX..............................
Midland, TX..................................
14.6
11.9
5.8
4.3
111.2
11.9
5.9
7.4
5.1
5.4
292.0
170.6
102.8
76.1
2,287.6
243.9
123.1
135.0
108.1
86.8
3.1
3.6
3.5
-4.2
0.8
2.5
0.4
2.4
1.9
-7.3
89
49
58
338
252
124
292
128
162
339
698
949
853
846
1,240
624
1,003
779
792
1,177
2.6
-0.3
3.5
-1.5
0.1
1.0
2.7
2.1
2.2
-6.7
154
323
72
337
319
300
147
215
204
341
See footnotes at end of table.
Table 1. Covered establishments, employment, and wages in the 343 largest counties,
third quarter 2015 - Continued
Average weekly wage ²
Employment
County¹
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15³
Ranking by
percent
change
Third
quarter
2015
Percent
change,
third quarter
2014-15³
Ranking by
percent
change
Montgomery, TX...........................
Nueces, TX..................................
Potter, TX.....................................
Smith, TX.....................................
Tarrant, TX...................................
Travis, TX.....................................
Webb, TX.....................................
Williamson, TX.............................
Davis, UT.....................................
Salt Lake, UT................................
10.5
8.2
4.0
6.1
41.1
37.3
5.1
9.5
8.0
42.4
165.3
163.0
79.1
100.2
844.9
692.4
97.7
150.8
119.8
649.8
3.2
0.8
1.6
4.1
2.6
4.6
2.6
4.5
3.5
3.6
81
252
192
25
117
15
117
16
58
49
$957
861
804
810
967
1,122
658
937
785
933
0.0
1.2
0.2
-0.6
2.5
3.9
0.9
1.7
2.7
4.1
320
286
318
329
165
47
305
253
147
37
Utah, UT.......................................
Weber, UT....................................
Chittenden, VT.............................
Arlington, VA................................
Chesterfield, VA...........................
Fairfax, VA....................................
Henrico, VA..................................
Loudoun, VA................................
Prince William, VA........................
Alexandria City, VA......................
14.6
5.8
6.6
9.4
8.6
37.1
11.2
11.6
9.1
6.7
211.7
98.7
101.7
171.3
131.8
589.0
188.3
156.0
123.3
96.4
6.3
3.3
0.9
3.0
5.7
2.0
4.1
5.3
4.1
1.6
2
71
243
95
4
151
25
7
25
192
767
744
928
1,587
833
1,462
945
1,126
860
1,372
2.8
3.2
1.8
1.5
1.1
1.2
2.5
2.0
2.1
2.2
138
91
247
265
294
286
165
228
215
204
Chesapeake City, VA...................
Newport News City, VA................
Norfolk City, VA...........................
Richmond City, VA.......................
Virginia Beach City, VA................
Benton, WA..................................
Clark, WA.....................................
King, WA......................................
Kitsap, WA....................................
Pierce, WA...................................
6.0
3.8
5.8
7.5
11.9
5.6
13.9
84.3
6.6
21.5
97.3
97.3
140.1
150.9
174.0
84.5
147.9
1,292.1
85.6
288.5
0.4
-0.1
0.1
1.8
1.5
3.3
3.8
3.4
2.3
1.9
292
317
311
172
204
71
42
66
137
162
766
957
1,002
1,089
767
965
915
1,463
921
898
2.8
3.1
2.9
4.1
2.5
3.1
3.0
1.0
2.4
3.6
138
104
129
37
165
104
117
300
178
64
Snohomish, WA............................
Spokane, WA...............................
Thurston, WA...............................
Whatcom, WA..............................
Yakima, WA.................................
Kanawha, WV...............................
Brown, WI.....................................
Dane, WI......................................
Milwaukee, WI..............................
Outagamie, WI.............................
20.1
15.5
7.8
7.1
7.7
5.9
6.7
14.7
25.7
5.1
277.8
211.6
107.1
84.9
121.3
102.6
152.3
322.8
484.9
105.4
2.8
1.8
2.3
1.8
(⁵)
-1.2
1.0
1.8
0.0
1.3
104
172
137
172
330
231
172
313
217
1,050
842
919
801
679
839
856
938
925
835
3.2
2.3
4.8
2.7
2.9
1.3
3.8
4.6
2.8
3.3
91
193
13
147
129
279
53
24
138
82
Waukesha, WI..............................
Winnebago, WI.............................
San Juan, PR...............................
12.6
3.7
10.6
237.0
90.6
250.4
1.3
0.7
0.4
217
266
(⁶)
953
888
614
3.8
3.1
1.7
53
104
(⁶)
¹ Includes areas not officially designated as counties. See Technical Note.
² Average weekly wages were calculated using unrounded data.
³ Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical
Note.
⁴ Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
⁵ Data do not meet BLS or state agency disclosure standards.
⁶ This county was not included in the U.S. rankings.
Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees
(UCFE) programs. These 342 U.S. counties comprise 72.2 percent of the total covered workers in the U.S.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
third quarter 2015
Average weekly wage ¹
Employment
County by NAICS supersector
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15²
Third
quarter
2015
Percent
change,
third quarter
2014-15²
United States³.................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
9,633.8
9,335.3
138.2
770.3
343.0
1,927.7
154.0
849.6
1,739.8
1,539.9
810.2
829.3
298.5
140,442.2
119,146.1
2,071.5
6,645.3
12,338.5
26,664.0
2,743.1
7,846.0
19,704.3
21,123.8
15,377.8
4,303.4
21,296.1
1.9
2.2
-6.3
4.0
0.7
2.1
1.1
1.9
2.3
2.3
3.0
1.4
0.5
$974
965
1,024
1,084
1,170
823
1,783
1,444
1,241
905
413
666
1,029
2.6
2.7
-4.7
4.2
1.8
2.6
2.7
3.7
3.0
2.7
3.5
3.7
2.5
Los Angeles, CA..............................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
457.6
451.6
0.5
13.6
12.4
53.7
9.8
24.9
48.0
211.3
31.6
27.8
6.0
4,261.8
3,707.3
8.6
127.9
357.2
803.0
202.6
212.8
595.8
731.3
488.8
147.2
554.4
2.2
2.3
-2.1
6.1
-1.5
1.8
0.9
1.3
0.8
2.7
2.9
0.9
1.5
1,074
1,035
1,344
1,129
1,167
876
1,957
1,717
1,317
821
591
691
1,348
3.7
3.4
-0.7
6.1
2.8
2.5
5.8
4.0
5.5
2.5
2.6
5.8
5.2
New York, NY..................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
129.9
129.0
0.0
2.2
2.2
20.2
4.9
19.2
27.4
9.8
13.7
20.4
0.8
2,370.4
2,107.5
0.2
38.0
27.3
257.3
151.6
367.7
542.5
326.8
284.4
99.7
263.0
2.1
2.2
-4.3
5.4
2.1
-0.9
0.6
1.6
3.3
1.8
2.3
0.7
1.2
1,829
1,892
1,928
1,789
1,346
1,276
2,571
3,292
2,122
1,309
854
1,098
1,312
2.5
2.4
-40.9
4.7
7.4
1.4
7.6
0.2
2.6
3.9
4.0
4.6
1.8
Cook, IL...........................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
165.4
164.1
0.1
13.6
6.8
32.5
2.8
16.5
35.2
17.1
15.0
18.8
1.3
2,535.6
2,240.3
1.1
73.3
186.6
467.5
55.0
188.0
465.6
432.6
270.1
95.0
295.3
1.5
1.7
18.4
2.4
0.4
1.9
2.2
0.6
1.3
1.5
3.1
-0.1
0.5
1,108
1,111
1,222
1,430
1,155
898
1,640
1,923
1,425
939
512
876
1,084
3.4
3.6
10.3
3.4
1.9
3.2
0.8
4.6
5.4
1.8
6.7
3.7
0.6
See footnotes at end of table.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
third quarter 2015 - Continued
Average weekly wage ¹
Employment
County by NAICS supersector
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15²
Third
quarter
2015
Percent
change,
third quarter
2014-15²
Harris, TX........................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
111.2
110.7
1.8
7.1
4.8
24.9
1.2
11.5
22.5
15.3
9.4
11.7
0.6
2,287.6
2,023.3
84.1
164.9
185.5
474.9
27.4
120.4
394.5
283.0
222.4
65.3
264.3
0.8
0.6
-11.5
3.2
-7.3
1.7
0.5
0.6
-0.6
4.7
5.3
2.6
2.3
$1,240
1,252
2,990
1,302
1,459
1,109
1,393
1,570
1,527
1,017
440
800
1,147
0.1
-0.2
-3.4
3.7
-2.1
0.5
1.0
4.7
1.3
4.6
5.0
6.4
2.5
Maricopa, AZ....................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
95.7
95.0
0.4
7.1
3.2
19.7
1.5
11.0
21.7
10.8
7.5
6.1
0.7
1,824.7
1,614.6
7.5
97.1
115.8
361.0
34.2
160.6
307.4
273.5
199.3
49.0
210.2
3.7
4.2
7.0
3.6
0.5
3.8
2.8
4.9
3.5
4.1
4.4
1.9
0.4
929
922
926
966
1,307
856
1,226
1,190
1,002
948
435
670
989
1.4
1.4
0.2
2.8
0.0
2.9
-0.6
4.1
0.2
1.4
0.5
3.4
1.7
Dallas, TX........................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
73.2
72.7
0.6
4.2
2.7
15.8
1.4
8.9
16.4
9.0
6.3
6.9
0.5
1,616.8
1,445.7
9.2
82.0
105.9
330.0
48.5
157.7
328.5
187.8
154.4
41.0
171.1
4.0
4.2
-2.8
6.2
-0.4
5.6
1.0
2.7
4.5
4.2
6.6
2.0
2.4
1,157
1,161
3,478
1,141
1,256
1,051
1,752
1,563
1,338
1,048
477
760
1,126
1.4
1.5
-9.2
5.0
-0.6
2.1
2.0
2.2
3.4
1.4
-0.6
-0.8
1.1
Orange, CA......................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
112.3
110.9
0.2
6.6
4.9
16.8
1.3
10.9
20.5
29.0
8.1
7.0
1.4
1,524.0
1,384.4
3.0
92.1
155.4
255.4
25.0
117.0
282.5
193.7
205.0
44.5
139.6
3.3
3.3
-8.9
8.9
0.1
1.2
0.6
3.6
1.5
4.2
4.0
2.4
3.7
1,077
1,062
831
1,221
1,321
943
1,654
1,666
1,284
907
468
674
1,237
2.1
2.0
1.7
4.6
1.9
1.3
1.2
5.2
0.8
2.6
2.9
4.3
2.9
See footnotes at end of table.
Table 2. Covered establishments, employment, and wages in the 10 largest counties,
third quarter 2015 - Continued
Average weekly wage ¹
Employment
County by NAICS supersector
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15²
Third
quarter
2015
Percent
change,
third quarter
2014-15²
San Diego, CA................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
104.5
102.7
0.7
6.5
3.1
14.3
1.2
9.6
18.2
29.0
7.8
7.4
1.8
1,384.0
1,157.0
9.7
71.5
104.8
215.7
23.5
70.9
229.5
187.4
185.3
50.3
227.0
2.9
3.2
-7.3
9.5
2.6
1.2
-4.4
2.9
2.4
3.5
2.6
1.8
1.4
$1,071
1,031
630
1,115
1,404
813
1,773
1,343
1,541
900
482
582
1,287
4.2
4.7
1.3
3.6
-0.1
3.7
1.6
6.3
8.4
3.1
5.9
2.6
2.4
King, WA.........................................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
84.3
83.8
0.4
6.2
2.4
14.6
2.1
6.5
16.4
19.4
6.9
8.9
0.5
1,292.1
1,129.2
3.1
64.8
107.0
243.4
91.3
66.7
216.6
161.5
132.1
42.7
162.9
3.4
3.4
18.1
7.0
-0.1
4.2
3.8
1.8
5.2
(⁴)
4.4
3.0
3.2
1,463
1,487
1,196
1,263
1,568
1,186
4,798
1,556
1,538
964
545
821
1,299
1.0
0.9
-5.2
4.2
1.9
5.3
-5.6
4.1
2.1
(⁴)
6.0
4.5
2.9
Miami-Dade, FL...............................................................
Private industry.............................................................
Natural resources and mining....................................
Construction...............................................................
Manufacturing............................................................
Trade, transportation, and utilities..............................
Information.................................................................
Financial activities......................................................
Professional and business services...........................
Education and health services...................................
Leisure and hospitality...............................................
Other services............................................................
Government..................................................................
93.2
92.8
0.5
5.7
2.7
25.9
1.4
9.9
20.0
9.9
6.8
8.0
0.3
1,076.1
940.9
7.0
40.4
39.1
274.1
17.6
73.7
147.7
168.7
131.0
39.8
135.2
2.8
3.2
-6.2
9.3
3.2
2.0
-2.6
3.5
5.0
2.5
2.6
5.1
-0.1
924
905
572
937
860
838
1,444
1,421
1,080
953
548
586
1,058
3.9
3.9
0.0
6.4
4.2
4.2
2.8
3.9
2.8
4.4
5.0
1.9
4.1
¹ Average weekly wages were calculated using unrounded data.
² Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Technical Note.
³ Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
⁴ Data do not meet BLS or state agency disclosure standards.
Note: Data are preliminary. Counties selected are based on 2014 annual average employment. Includes workers covered by Unemployment Insurance
(UI) and Unemployment Compensation for Federal Employees (UCFE) programs.
Table 3. Covered establishments, employment, and wages by state,
third quarter 2015
Average weekly wage ¹
Employment
State
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15
Third
quarter
2015
Percent
change,
third quarter
2014-15
United States²..........................................
9,633.8
140,442.2
1.9
$974
2.6
Alabama....................................................
Alaska........................................................
Arizona......................................................
Arkansas...................................................
California...................................................
Colorado....................................................
Connecticut...............................................
Delaware...................................................
District of Columbia...................................
Florida.......................................................
119.6
22.5
152.6
88.3
1,436.2
187.9
116.5
30.6
38.2
644.2
1,893.6
346.4
2,613.9
1,193.4
16,474.4
2,513.0
1,668.3
436.3
743.6
8,023.2
1.2
0.4
2.9
1.9
3.0
2.9
0.2
2.1
1.4
3.5
830
1,041
889
756
1,134
1,006
1,147
963
1,667
852
1.8
2.2
1.5
2.6
3.4
2.4
2.0
0.3
2.3
3.1
Georgia......................................................
Hawaii........................................................
Idaho.........................................................
Illinois........................................................
Indiana.......................................................
Iowa...........................................................
Kansas......................................................
Kentucky....................................................
Louisiana...................................................
Maine.........................................................
291.9
39.8
55.9
432.2
160.3
101.2
87.6
122.3
127.4
51.3
4,171.1
635.4
680.3
5,888.6
2,971.7
1,535.9
1,370.9
1,852.5
1,926.3
609.7
2.8
1.4
3.3
1.3
1.6
0.4
0.6
1.4
-0.2
0.7
916
896
736
1,020
818
823
809
804
858
779
2.8
3.1
2.1
3.9
2.4
3.0
1.8
2.9
0.7
3.3
Maryland....................................................
Massachusetts..........................................
Michigan....................................................
Minnesota..................................................
Mississippi.................................................
Missouri.....................................................
Montana....................................................
Nebraska...................................................
Nevada......................................................
New Hampshire.........................................
167.6
241.6
242.0
159.4
72.1
193.3
45.5
72.6
79.0
51.3
2,607.8
3,446.9
4,203.0
2,800.7
1,118.9
2,737.9
457.9
964.0
1,254.5
642.8
1.3
1.4
1.6
1.4
1.2
1.9
1.9
1.4
3.2
1.5
1,067
1,197
921
990
706
846
759
811
862
952
2.4
3.0
2.7
2.6
1.3
2.2
3.7
4.2
2.5
2.7
New Jersey...............................................
New Mexico...............................................
New York..................................................
North Carolina...........................................
North Dakota.............................................
Ohio...........................................................
Oklahoma..................................................
Oregon......................................................
Pennsylvania.............................................
Rhode Island.............................................
265.4
57.0
639.5
267.8
32.3
291.4
109.4
144.8
353.4
36.6
3,933.9
809.2
9,065.4
4,194.1
438.0
5,282.7
1,598.0
1,812.8
5,722.1
477.4
1.4
0.6
1.8
2.5
-3.8
1.2
0.2
3.0
0.8
1.2
1,116
798
1,180
863
956
878
825
924
961
919
2.6
1.3
3.1
3.0
-2.3
1.9
0.0
4.4
2.5
2.6
South Carolina..........................................
South Dakota............................................
Tennessee.................................................
Texas.........................................................
Utah...........................................................
Vermont.....................................................
Virginia......................................................
Washington...............................................
West Virginia.............................................
Wisconsin..................................................
123.5
32.6
150.8
640.7
94.1
24.8
258.8
235.4
50.1
168.5
1,959.7
419.5
2,850.6
11,681.0
1,353.9
308.2
3,759.7
3,187.6
702.4
2,815.7
2.9
0.9
2.7
2.1
3.7
0.5
2.5
2.5
-1.1
0.9
788
756
864
999
829
829
1,014
1,111
785
834
2.6
3.1
3.2
1.1
3.2
3.0
2.5
2.2
0.9
3.5
See footnotes at end of table.
Table 3. Covered establishments, employment, and wages by state,
third quarter 2015 - Continued
Average weekly wage ¹
Employment
State
Establishments,
third quarter
2015
(thousands)
September
2015
(thousands)
Percent
change,
September
2014-15
Third
quarter
2015
Percent
change,
third quarter
2014-15
Wyoming...................................................
26.2
287.4
-1.5
$866
-1.1
Puerto Rico...............................................
Virgin Islands............................................
45.4
3.4
891.1
36.8
-0.7
-2.1
512
738
1.4
2.1
¹ Average weekly wages were calculated using unrounded data.
² Totals for the United States do not include data for Puerto Rico or the Virgin Islands.
Note: Data are preliminary. Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for
Federal Employees (UCFE) programs.
Chart 3. Percent change in employment in counties with 75,000 or more employees,
September 2014-15 (U.S. average = 1.9 percent)
Largest Counties
Higher than U.S. average
U.S. average or lower
Source: Bureau of Labor Statistics
Chart 4. Percent change in average weekly wage in counties with 75,000 or more
employees, third quarter 2014-15 (U.S. average = 2.6 percent)
Largest Counties
Higher than U.S. average
U.S. average or lower
Source: Bureau of Labor Statistics